provides a global platform and social
creators reach consumers directly.
would improve their work or lives.
network to foster discovery and
There is no middle man that tells
Examples of APIs offered in the
community collaboration. To improve
app developers what to build. They
marketplace today include those
the user experience, Mendeley was
publish to an online marketplace and
offering recommendations for similar
looking to anticipate the behavior of
consumers select what's best or most
products purchased, detecting
new users in their initial adoption
relevant for their needs.
anomalies in data, and performing
and engagement phase. Within
two weeks of implementing Azure
Machine Learning, developers were
able to create a predictive model
that was 30% more accurate than an
earlier model that had taken them
months to develop on their own. Not
only is Mendeley able to iterate and
deploy models three to five times
faster, it can pinpoint users' needs
with much greater confidence.
We are trying to emulate this by
adding machine learning models and
packages to the Azure Marketplace: a
marketplace where data scientists can
show their creativity and monetize it.
By "data scientists" I mean engineers
and physicists and statisticians and
business school graduates who love
data, are passionate about developing
analytical models, but haven't had the
tools to build full solutions.
Building the Data Science
Economy
With a ready-made marketplace to
We're beginning to see what happens
can develop innovative analytical
when we make machine learning
models, package them into APIs
accessible to enterprises. But what
(application program interfaces)
about making machine learning in
that others can consume, and
the cloud available to individuals?
publish these APIs. Developers and
I'm thinking here mostly about
consumers can then access the same
the supply side of the market for
marketplace, search or browse for
advanced analytics.
APIs, and pay for a specific API they
The cloud as a platform has already
given us the app economy, where app
showcase their skills, data scientists
wish to consume - something that
they would, in turn, use to deliver
sentiment analysis on textual data
such as social media feeds or web
pages. These marketplace APIs can
be consumed in other applications
or even in Excel spreadsheets.
They support transactions in many
currencies and offer an efficient
platform for building a data science
economy. We expect eventually to
host millions of such analytics APIs
in the cloud.
Machine learning is poised to be
a game changer across industries
and an important technology for
improving our personal lives. We
are rapidly realizing the vision of
democratizing the use of machine
learning by both enterprises and
individuals. Businesses should take
the time now to understand the true
potential of machine learning and
advanced analytics within their
own organizations.
a predictive analytics solution that
The Takeaways
* Machine learning - a branch of artificial intelligence that involves advanced statistics - is a tool for
training computers to make data-based predictions. When you can make accurate predictions, you have
the power to optimize business systems and processes.
* Thanks to the explosion of big data and the advent of cloud computing, machine learning is now
accessible to a wide array of organizations and may soon touch many aspects of our lives, as Microsoft is
exploring in its Intelligent Cloud project.
* Machine learning may be a game changer for businesses and individuals. Now is the time to learn about its potential.
CTO Straight Talk | 38

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